Every business is unique, as are its data and problems. In order to make the most of our valuable data, we need to incorporate these intricacies when building a solution. Bayesian modeling provides a powerful framework for building a so-called digital twin that maps our real-world problem and domain-expertise into a statistical model that can then be fit to data. The benefits are that our solutions are transparent and interpretable by stakeholders, and come with uncertainty measures.

In this talk I will give a few examples of real-world business problems and how Bayesian modeling can solve them. In particular, some common patterns observed in business data sets are time-series, hierarchical or nested structure, and spatial data.

In this talk I will give a few examples of real-world business problems and how Bayesian modeling can solve them. In particular, some common patterns observed in business data sets are time-series, hierarchical or nested structure, and spatial data.